如何使用TensorFlow java api删除预训练模型的输出层？

我有像Inception-v3这样的预训练模型 . 我想删除输出图层并在图像认知中使用它 . 以下是tensorflow给出的示例：

就像python框架Keras一样，它有一个像 model.layers.pop() 这样的方法 . 我试过用tensorflow java api做的 . 首先我尝试使用dl4j，但是当我导入keras模型时，我得到了这样的错误：

2017-06-15 21:15:43 INFO  KerasInceptionV3Net:52 - Importing Inception model from data/inception-model.json
2017-06-15 21:15:43 INFO  KerasInceptionV3Net:53 - Importing Weights model from data/inception_v3_complete
Exception in thread "main" java.lang.RuntimeException: Unknown exception.
at org.bytedeco.javacpp.hdf5$H5File.allocate(Native Method)
at org.bytedeco.javacpp.hdf5$H5File.<init>(hdf5.java:12713)
at org.deeplearning4j.nn.modelimport.keras.Hdf5Archive.<init>(Hdf5Archive.java:61)
at org.deeplearning4j.nn.modelimport.keras.KerasModel$ModelBuilder.weightsHdf5Filename(KerasModel.java:603)
at org.deeplearning4j.nn.modelimport.keras.KerasModelImport.importKerasModelAndWeights(KerasModelImport.java:176)
at edu.usc.irds.dl.dl4j.examples.KerasInceptionV3Net.<init>(KerasInceptionV3Net.java:55)
at edu.usc.irds.dl.dl4j.examples.KerasInceptionV3Net.main(KerasInceptionV3Net.java:108)
HDF5-DIAG: Error detected in HDF5 (1.10.0-patch1) thread 0:
#000: C:\autotest\HDF5110ReleaseRWDITAR\src\H5F.c line 579 in H5Fopen(): unable to open file
major: File accessibilty
minor: Unable to open file
#001: C:\autotest\HDF5110ReleaseRWDITAR\src\H5Fint.c line 1100 in H5F_open(): unable to open file: time = Thu Jun 15 21:15:44 2017,name = 'data/inception_v3_complete', tent_flags = 0
major: File accessibilty
minor: Unable to open file
#002: C:\autotest\HDF5110ReleaseRWDITAR\src\H5FD.c line 812 in H5FD_open(): open failed
major: Virtual File Layer
minor: Unable to initialize object
#003: C:\autotest\HDF5110ReleaseRWDITAR\src\H5FDsec2.c line 348 in H5FD_sec2_open(): unable to open file: name = 'data/inception_v3_complete', errno = 2, error message = 'No such file or directory', flags = 0, o_flags = 0
major: File accessibilty
minor: Unable to open file

所以我回到了tensorflow . 我将在keras中修改模型并将模型转换为张量 . 这是我的转换脚本：

input_fld = './'
output_node_names_of_input_network = ["pred0"]
write_graph_def_ascii_flag = True
output_node_names_of_final_network = 'output_node'   
output_graph_name = 'test2.pb'
from keras.models import load_model
import tensorflow as tf
import os
import os.path as osp
from keras.applications.inception_v3 import InceptionV3
from keras.applications.vgg16 import VGG16
from keras.models import Sequential
from keras.layers.core import Flatten, Dense, Dropout
from keras.layers.convolutional import Convolution2D, MaxPooling2D, ZeroPadding2D
from keras.optimizers import SGD
output_fld = input_fld + 'tensorflow_model/'
if not os.path.isdir(output_fld):
    os.mkdir(output_fld)
net_model = InceptionV3(weights='imagenet', include_top=True)
num_output = len(output_node_names_of_input_network)
pred = [None]*num_output
pred_node_names = [None]*num_output
for i in range(num_output):
    pred_node_names[i] = output_node_names_of_final_network+str(i)
    pred[i] = tf.identity(net_model.output[i], name=pred_node_names[i])
print('output nodes names are: ', pred_node_names)
from keras import backend as K
sess = K.get_session()

if write_graph_def_ascii_flag:
    f = 'only_the_graph_def.pb.ascii'
    tf.train.write_graph(sess.graph.as_graph_def(), output_fld, f, as_text=True)
print('saved the graph definition in ascii format at: ', osp.join(output_fld, f))
from tensorflow.python.framework import graph_util
from tensorflow.python.framework import graph_io

constant_graph = graph_util.convert_variables_to_constants(sess, sess.graph.as_graph_def(), pred_node_names)
graph_io.write_graph(constant_graph, output_fld, output_graph_name, as_t  ext=False)
print('saved the constant graph (ready for inference) at: ', osp.join(output_fld, output_graph_name))

我把模型作为.pb文件，但当我把它放入张量示例The LabelImage example时，我收到了这个错误：

Exception in thread "main" java.lang.IllegalArgumentException: You must feed a value for placeholder tensor 'batch_normalization_1/keras_learning_phase' with dtype bool
 [[Node: batch_normalization_1/keras_learning_phase = Placeholder[dtype=DT_BOOL, shape=<unknown>, _device="/job:localhost/replica:0/task:0/cpu:0"]()]]
at org.tensorflow.Session.run(Native Method)
at org.tensorflow.Session.access$100(Session.java:48)
at org.tensorflow.Session$Runner.runHelper(Session.java:285)
at org.tensorflow.Session$Runner.run(Session.java:235)
at com.dlut.cmh.sheng.LabelImage.executeInceptionGraph(LabelImage.java:98)
at com.dlut.cmh.sheng.LabelImage.main(LabelImage.java:51)

我不知道如何解决这个问题 . 谁能帮我？或者你有另一种方法可以做到这一点？